Stabilizing switching control for nonlinear system based on quasi-ARX RBFN model

Lan Wang, Yu Cheng, Jinglu Hu*

*この研究の対応する著者

研究成果査読

8 被引用数 (Scopus)

抄録

In this paper, a fuzzy switching adaptive control approach is presented for nonlinear systems. The proposed fuzzy switching adaptive control law is composed of a quasi-ARX radial basis function network (RBFN) prediction model and a fuzzy switching mechanism. The quasi-ARX RBFN prediction model consists of two parts: a linear part used for a linear controller to ensure boundedness of the input and output signals; and an RBFN nonlinear part used to improve control accuracy. By using the fuzzy switching scheme between the linear and nonlinear controllers to replace the 0/1 switching, it can realize a better balance between stability and accuracy. Theoretical analysis and simulation results show the effectiveness of the proposed control method on the stability, accuracy, and robustness.

本文言語English
ページ(範囲)390-396
ページ数7
ジャーナルIEEJ Transactions on Electrical and Electronic Engineering
7
4
DOI
出版ステータスPublished - 2012 7

ASJC Scopus subject areas

  • 電子工学および電気工学

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